# Fashion++: Minimal Edits for Outfit Improvement

arXiv: https://arxiv.org/abs/1904.09261 · HTML: https://mlsanity.com/paper/1904.09261/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Apr 2019.

## Built on by (most cited first, 20 of 20)

- [Kaleido-BERT: Vision-Language Pre-training on Fashion Domain](https://mlsanity.com/paper/2103.16110/) (2021)
- [Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing](https://mlsanity.com/paper/2104.07021/) (2021)
- [Point-Based Modeling of Human Clothing](https://mlsanity.com/paper/2104.08230/) (2021)
- [Toward Accurate and Realistic Outfits Visualization with Attention to Details](https://mlsanity.com/paper/2106.06593/) (2021)
- [CT-Net: Complementary Transfering Network for Garment Transfer with Arbitrary Geometric Changes](https://mlsanity.com/paper/2105.05497/) (2021)
- [Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis](https://mlsanity.com/paper/2109.02081/) (2021)
- [Masked Vision-Language Transformer in Fashion](https://mlsanity.com/paper/2210.15110/) (2022)
- [From Culture to Clothing: Discovering the World Events Behind A Century of Fashion Images](https://mlsanity.com/paper/2102.01690/) (2021)
- [Detours for Navigating Instructional Videos](https://mlsanity.com/paper/2401.01823/) (2024)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)
- [Arbitrary Virtual Try-On Network: Characteristics Preservation and Trade-off between Body and Clothing](https://mlsanity.com/paper/2111.12346/) (2021)
- [Modern Augmented Reality: Applications, Trends, and Future Directions](https://mlsanity.com/paper/2202.09450/) (2022)
- [ACDG-VTON: Accurate and Contained Diffusion Generation for Virtual Try-On](https://mlsanity.com/paper/2403.13951/) (2024)
- [COutfitGAN: Learning to Synthesize Compatible Outfits Supervised by Silhouette Masks and Fashion Styles](https://mlsanity.com/paper/2502.08674/) (2025)
- [fAshIon after fashion: A Report of AI in Fashion](https://mlsanity.com/paper/2105.03050/) (2021)
- [DiCTI: Diffusion-based Clothing Designer via Text-guided Input](https://mlsanity.com/paper/2407.03901/) (2024)
- [Partial Visual-Semantic Embedding: Fashion Intelligence System with Sensitive Part-by-Part Learning](https://mlsanity.com/paper/2211.06688/) (2022)
- [Wearing the Same Outfit in Different Ways -- A Controllable Virtual Try-on Method](https://mlsanity.com/paper/2211.16989/) (2022)
- [ControlEdit: A MultiModal Local Clothing Image Editing Method](https://mlsanity.com/paper/2409.14720/) (2024)
- [Fashionability-Enhancing Outfit Image Editing with Conditional Diffusion Models](https://mlsanity.com/paper/2412.18421/) (2024)

## Abstract (arXiv)

Given an outfit, what small changes would most improve its fashionability? This question presents an intriguing new vision challenge. We introduce Fashion++, an approach that proposes minimal adjustments to a full-body clothing outfit that will have maximal impact on its fashionability. Our model consists of a deep image generation neural network that learns to synthesize clothing conditioned on learned per-garment encodings. The latent encodings are explicitly factorized according to shape and texture, thereby allowing direct edits for both fit/presentation and color/patterns/material, respectively. We show how to bootstrap Web photos to automatically train a fashionability model, and develop an activation maximization-style approach to transform the input image into its more fashionable self. The edits suggested range from swapping in a new garment to tweaking its color, how it is worn (e.g., rolling up sleeves), or its fit (e.g., making pants baggier). Experiments demonstrate that Fashion++ provides successful edits, both according to automated metrics and human opinion. Project page is at http://vision.cs.utexas.edu/projects/FashionPlus.